BalbC scRNA-seq analysis
2024-03-13
#Loading libraries
Merged Seurat Object
#Loading merged seurat object
This analysis was carried out on the 3 experiments: 230303, 230320, 230327. In these experiments, we used OT-II Ptendel BALB/c mice, corresponding to OT-II Ptendel C57BL/6J(B6) mice crossed with BALB/c mice. Based on the clinical status of mice and FACS analysis we categorized the T cell leukemic development into three major stages: pre-leukemic ‘early’, pre-leukemic ‘late’ and leukemic. Then, we performed a CITE-seq assays on the thymus and spleen of 3 control OT-II BALB/c mice and 9 OT-II Ptendel BALB/c mice (1 mouse from ‘pre-leukemic’early ; 5 mice from pre-leukemic ’late’ and 3 mice from leukemic stages).
p1 <- VlnPlot(bc.combined.cc,features = "nFeature_RNA", group.by = "orig.ident", pt.size = 0.1)
p2 <- VlnPlot(bc.combined.cc,features = "percent.ribo", group.by = "orig.ident", pt.size = 0.1)
plot_grid(p1, p2, ncol = 2)
#Results of data demultiplexing
DimPlot(bc.combined.cc, group.by = "MULTI_ID", reduction = "wnn.umap", pt.size = 0.5, label = TRUE, repel = TRUE, label.size = 2.5)
#Leukemia stages
annotation.palette1 <- c("#ECD078FF","#DA5B43FF", "#C12942FF","#AF1900FF")
annotation.palette2 <- c("#80D0D0FF", "#50A8B0FF" , "#3870A0FF","#284878FF")
names(annotation.palette1) <- c("Thymus-WT","Thymus-PreTum early","Thymus-PreTum late","Thymus-Tum")
names(annotation.palette2) <- c("Spleen-WT","Spleen-PreTum early","Spleen-PreTum late","Spleen-Tum")
DimPlot(bc.combined.cc, group.by = "annotation", reduction = "wnn.umap",cols = c(annotation.palette1,annotation.palette2), pt.size = 0.2, label = TRUE, repel = T, label.size = 4, label.color = "#0D0C0BFF")
DimPlot(bc.combined.cc, group.by = "MULTI_ID", split.by = "annotation", reduction = "wnn.umap", pt.size = 0.2, label = TRUE, repel = T, label.size = 4,ncol=4, label.color = "#0D0C0BFF")
#Clustering
DimPlot(bc.combined.cc, group.by = "wsnn_res.2", reduction = "wnn.umap" , pt.size = 0.5, label = TRUE, repel = TRUE)
WT subset analysis
load(file = "/mnt/NASBIOINFO_CP/LALT/BIOINFO/PTEN/03_Analysis/Analysis2024/RObject/miceWT_2023_merged.Robj")
DefaultAssay(miceWT) <- 'RNA'
Idents(miceWT) <- "wsnn_res.0.6"
DimPlot(miceWT, reduction = "wnn.umap", group.by = "wsnn_res.0.6", label = T, label.size = 6)
FeaturePlot(miceWT, reduction = "wnn.umap", features = c("adt_CD25","Il2ra","Mki67","adt_CD8","adt_CD4","adt_CD3","adt_CD62L","adt_CD69","Myc","adt_TCRgd","Rag1","adt_CCR7")) & scale_colour_gradientn(colours = (viridis::rocket(10, direction = -1)))
Idents(miceWT)<-"wsnn_res.0.6"
miceWT@active.ident <- factor(miceWT@active.ident,levels=c("6","11","14","5","0","7","2","1","15","10","4","9","3","8","12","13"))
genes <- c("Ptcra","Il2ra","adt_CD25","Top2a","Mki67","Rag1","Cd3d","adt_CD3","Cd4","adt_CD4","Cd8a","adt_CD8","Ccr9","Cd69","adt_CD69","Ccr7","adt_CCR7","Sell","Nkg7","Gzma","Ccl5","Klrc1","Trdc","adt_TCRgd")
p3 <- DotPlot(miceWT, features = genes) + geom_point(aes(size=pct.exp), shape = 21, colour="black", stroke=0.5) + scale_colour_gradient2(low = "steelblue", mid = "ivory1", high = "red") + guides(size=guide_legend(override.aes=list(shape=21, colour="black", fill="white"))) + RotatedAxis() + coord_flip()+ labs(title = "Expression of marker genes by clusters")
p4 <- DimPlot(miceWT, reduction = "wnn.umap", group.by = "wsnn_res.0.6", label = T, label.size = 6) + labs(title = "UMAP Visualization of Clusters in WT Mice")
plot_grid(p3, p4, ncol = 2)
WT.palette <- c('#59A5A9FF', '#60AB9EFF', '#69B190FF', '#77B77DFF', '#8CBC68FF', '#A6BE54FF', '#BEBC48FF', '#D1B541FF', '#DDAA3CFF', '#E49C39FF', '#E78C35FF' )
names(WT.palette) <- c("DN", "DPsm-CD25+", "DPsm-CCR7+", "DPblast", "DPsm", "DP69int", "DP69+", "SP4","SP8", "Tgd", "NK")
DimPlot(miceWT,reduction = "wnn.umap", group.by = "manual.annotation", label = T, cols = WT.palette , pt.size = 0.2,label.size = 3 )
#ScigeneX reveals co-expressed gene modules across cell populations
# # Select informative genes
# miceWT_scigenex20.3 <- select_genes(miceWT,
# k = 20,
# distance_method = "pearson",
# which_slot = "data",
# row_sum=2)
#
# # Run MCL
# miceWT_scigenex20.3 <- gene_clustering(miceWT_scigenex20.3,
# s = 5,
# threads = 2,
# inflation = 3)
load(file= "/mnt/NASBIOINFO_CP/LALT/BIOINFO/PTEN/03_Analysis/Analysis2024/RObject/miceWT_scigenex20.3.Robj")
miceWT_scigenex20.3@gene_clusters## $`1`
## [1] "Ms4a4b" "Gm2682" "Klf2" "H2-D1"
## [5] "H2-K1" "AW112010" "Gimap3" "H2-Q6"
## [9] "B2m" "Cnn2" "Shisa5" "Tmsb10"
## [13] "Gimap4" "Ms4a6b" "Itgb7" "Fxyd5"
## [17] "Ccr7" "Cd52" "Cd53" "S1pr1"
## [21] "Il7r" "Ripor2" "Hcst" "Lcp1"
## [25] "B4galnt1" "Sidt1" "Gramd3" "Samhd1"
## [29] "Tagln2" "Evl" "Slfn1" "Vim"
## [33] "Klk8" "Ccnd2" "Rflnb" "Cdk2ap2"
## [37] "Ltb" "Inpp4b" "Psme2" "Bcl2"
## [41] "Cd2" "Add3" "Psmb9" "Ifi27l2a"
## [45] "Cotl1" "Kbtbd11" "Gpr183" "Anxa6"
## [49] "Atp1b3" "Bin2" "Gpr18" "Stat1"
## [53] "Cxcr3" "Sell" "Ptpn18" "Psme1"
## [57] "Srgn" "Pik3cd" "Tpst2" "Irf1"
## [61] "Rasa3" "Il27ra" "Lfng" "Smc6"
## [65] "Gm8369" "Ifi47" "Glipr2" "Stat4"
## [69] "Cytip" "Arl4c" "Aldoa" "Gm45552"
## [73] "Cd226" "Pde2a" "Ctss" "Smpdl3a"
## [77] "Chd3" "Sp100" "Ppp1r18" "Ppp3cc"
## [81] "Stk10" "Bach2" "Junb" "Tapbp"
## [85] "Sema4a" "Igfbp4" "Dapl1" "Il6ra"
## [89] "Ifi208" "Vasp" "Gimap5" "Ly6a"
## [93] "Chd7" "Cd82" "Rapgef6" "Clec2d"
## [97] "Prkch" "Sgk1" "Jak1" "Ass1"
## [101] "Atp8b4" "BE692007" "Msn" "Esyt1"
## [105] "Smad7" "Emp3" "Ostf1" "Sntb1"
## [109] "Arrb2" "Pde3b" "Phf11b" "Selplg"
## [113] "Arpc1b" "Foxo1" "Plaat3" "Cmah"
## [117] "Epsti1" "Cd48" "Dock10" "Pced1b"
## [121] "Itgb2" "Tnfaip8l2" "Itga4" "Ttc39b"
## [125] "Runx3" "Tagap" "Gstp3" "Tes"
## [129] "Arl6ip5" "Jun" "Cyth4" "Sgms1"
## [133] "Tnfsf8" "Vsir" "Ier2" "Il10rb"
## [137] "S1pr4" "Fos" "Ms4a6d" "Myh9"
## [141] "Tpm4" "Pitpnc1" "Scml4" "Ndfip1"
## [145] "Zfp36l2" "Dtx1" "Gimap7" "Nlrc5"
## [149] "Cd69" "Fyn" "Ehd3" "Crip1"
## [153] "Traf1" "Ifngas1" "Psmb10" "Dennd2d"
## [157] "Stk17b" "Irf7" "Slc17a9" "Rps27rt"
## [161] "Fam102a" "Tgtp2" "Il2rg" "Card6"
## [165] "Prkcq" "Rgs3" "Ncf4" "Neurl3"
## [169] "Flt3l" "Arhgef3" "Sh2d3c" "Utrn"
## [173] "Golm1" "Prelid2" "Pde7a" "Otulinl"
## [177] "Dock2" "Bin1" "Actr3" "Tmem173"
## [181] "9930111J21Rik2" "Ipcef1" "Tent5c" "H2-T23"
## [185] "Dipk1a" "Nod1" "Crtam" "Rabac1"
##
## $`2`
## [1] "Ccna2" "Nusap1" "Birc5" "Cdca3"
## [5] "Knl1" "Mxd3" "Tpx2" "Cenpf"
## [9] "Plk1" "Ckap2l" "Kif11" "Ube2c"
## [13] "Cdk1" "Esco2" "Aurkb" "Prc1"
## [17] "Mki67" "Cdca8" "Cenpe" "Ccnf"
## [21] "Tacc3" "Spc25" "Ccnb2" "Sgo2a"
## [25] "Hmmr" "Depdc1a" "Shcbp1" "Ttk"
## [29] "Kif15" "Ccnb1" "Bub1" "Kif20a"
## [33] "Cks2" "Neil3" "Ncapg" "Aurka"
## [37] "Kif22" "Aspm" "Depdc1b" "Melk"
## [41] "Anln" "Ndc80" "Mis18bp1" "Pimreg"
## [45] "Cdc20" "Foxm1" "Racgap1" "Kif18b"
## [49] "Hist1h2ae" "Kif4" "Cep55" "Bub1b"
## [53] "Nuf2" "Lockd" "Sgo1" "Parpbp"
## [57] "Ska1" "Cks1b" "Cdca2" "Ect2"
## [61] "Cdca5" "Cenpm" "Kif14" "Nek2"
## [65] "Kif2c" "Stil" "Incenp" "Cenpa"
## [69] "Ncaph" "Hmgn2" "Cenpp" "Diaph3"
## [73] "Spag5" "Pif1" "Ncapd2" "Cdkn3"
## [77] "Kpna2" "Gm4316" "Arhgef39" "Prr11"
## [81] "H2afx" "Ska3" "Smc2" "Kifc1"
## [85] "Cip2a" "Kif23" "Mad2l1" "Ankle1"
## [89] "Knstrn" "BC030867" "Cit" "Cdc25c"
## [93] "Plk4" "Arhgap11a" "Tmpo" "Hist1h1b"
## [97] "Hist1h2ak" "Dlgap5" "Sapcd2" "Rtkn2"
## [101] "Ptma" "Ckap2" "Gtse1" "Mastl"
## [105] "Gm20628" "Hist1h2ap" "Kntc1" "Kif18a"
## [109] "Hmgb3" "Ube2s" "Espl1" "Cenpi"
## [113] "Anp32e" "Kif20b" "Hist1h2af" "Hist1h3c"
## [117] "Lmnb1" "Iqgap3" "Nucks1" "Cdkn2c"
## [121] "Hist2h2ac" "Efcab11" "Selenoh" "Tubb4b"
## [125] "Troap" "Hist2h2bb" "Fam83d" "Hmgn5"
## [129] "Zwilch" "Mtfr2" "Trip13" "Poc1a"
## [133] "Cenpl" "Kifc5b" "CAAA01147332.1" "Psrc1"
## [137] "Hist1h3g" "Ckap5" "Hist1h4d" "2610318N02Rik"
## [141] "Eme1" "Pttg1" "H2afv" "Hist1h1d"
## [145] "Hist1h1e" "Neurl1b" "Arhgap19" "Tubb5"
## [149] "Trim59" "Cdc25b" "Spdl1" "Ska2"
## [153] "Dbf4" "Hist1h2bm" "Eldr" "H1fx"
## [157] "Gas2l3" "Emp1" "Bora" "Nde1"
## [161] "Hist1h3i" "Hist2h4" "Mns1" "Tuba1c"
## [165] "Rad21" "Traip" "Hist1h2bl" "Hist1h3e"
## [169] "Fzr1" "Ddah2" "Hist1h2bj" "Bard1"
## [173] "Dsn1" "Gen1" "Lsm5"
##
## $`3`
## [1] "Top2a" "Pclaf" "Spc24" "Rrm2" "Fbxo5" "Clspn"
## [7] "E2f8" "Rad51ap1" "Tyms" "Tk1" "Hmgb2" "Asf1b"
## [13] "Ncapg2" "Lig1" "E2f7" "Uhrf1" "Rrm1" "Cdc45"
## [19] "Mcm5" "Hist1h1a" "Tuba1b" "Rad51" "Tcf19" "Mybl2"
## [25] "Oip5" "Gmnn" "Stmn1" "Syce2" "Cenpk" "Cdc6"
## [31] "Ccne2" "Fignl1" "Pcna" "Nt5dc2" "Tipin" "Cenpw"
## [37] "H2afz" "Gm10282" "Dut" "Cenpn" "Cenph" "Mcm10"
## [43] "Dhfr" "Fabp5" "Mcm3" "Mcm6" "Siva1" "Slbp"
## [49] "Rfc4" "Chaf1a" "Dnph1" "Pole" "Prim1" "Dek"
## [55] "Pola1" "Lrr1" "Rcc1" "Ticrr" "Hells" "Nsd2"
## [61] "Hirip3" "Aunip" "Brca1" "Dctpp1" "Atad2" "Tfdp1"
## [67] "Dna2" "Ccdc34" "Ran" "Brip1" "Fen1" "Nap1l1"
## [73] "Lsm2" "Rad54l" "Fancd2" "Exo1" "Ezh2" "Gins2"
## [79] "Ranbp1" "Alyref" "Chtf18" "Cenps" "Slc43a3" "Usp1"
## [85] "Anp32b" "Acot7" "Pold1" "Psat1" "Chek1" "Snrpd1"
## [91] "Pkmyt1" "Ube2t" "Rfc5" "Gins1" "Phgdh" "Fxn"
## [97] "Nrm" "Dnmt1" "Mcm7" "Ung" "Dscc1" "Timeless"
## [103] "Zfp367" "Rpa2" "Snrpf" "E2f1" "Nasp" "Ercc6l"
## [109] "Shmt1" "Pask" "Banf1" "Orc6" "Rad54b" "Hsp90aa1"
## [115] "Tmem107" "Pa2g4" "Tpi1" "Mcm2" "Dnajc9" "Hmga1"
## [121] "Ncapd3" "Mcm4" "Nelfe" "Wdhd1" "Ccne1" "Rnaseh2b"
## [127] "Ppil1" "Cntln" "Chaf1b" "Atad5" "Rfc3" "Pmf1"
## [133] "Rps27l" "Blm" "Snu13" "Lsm6" "Slc29a1" "Rpa3"
## [139] "Atpif1" "Rbbp7" "Ptges3" "Nutf2" "Dbi" "Ssrp1"
## [145] "Hnrnpa3"
##
## $`4`
## [1] "Rps24" "Rps16" "Rps20" "Fau"
## [5] "Rps7" "Rps10" "Rps15a" "Rps4x"
## [9] "Rpl13" "Rps8" "Rps5" "Rps3a1"
## [13] "Rpsa" "Rpl9" "Rps27a" "Rplp0"
## [17] "Rpl19" "Rpl23" "Rpl32" "Rpl18a"
## [21] "Rpl30" "Rpl18" "Rps13" "Rps3"
## [25] "Rps14" "Rps26" "Rpl39" "Rpl37"
## [29] "Rpl21" "Rpl34" "Rpl41" "Rpl8"
## [33] "Rplp1" "Tpt1" "Rpl17" "Rplp2"
## [37] "Rpl27a" "Rps11" "Rpl6" "Rps21"
## [41] "Rps19" "Rpl12" "Rpl35a" "Rpl10"
## [45] "Rpl11" "Rpl22" "Rps2" "Rps28"
## [49] "Rpl10a" "Rps23" "Rpl36a" "Rps9"
## [53] "Rpl36" "Rpl28" "Gm10260" "Rps27"
## [57] "Rpl15" "Rpl3" "Rpl37a" "Rps12"
## [61] "Nme2" "Rpl13a" "Eef1b2" "Rps29"
## [65] "Rpl38" "Rpl35" "Rpl24" "Rack1"
## [69] "Rpl29" "Rpl14" "Rpl7" "Rps6"
## [73] "Rpl22l1" "Rpl26" "Rpl27" "Rpl5"
## [77] "Rpl7a" "Naca" "Eef2" "Rps15"
## [81] "Npm1" "Rac2" "Rpl23a" "Rpl4"
## [85] "Rpl36al" "Rps25" "Pabpc1" "Eif3f"
## [89] "Atp5g2" "Rpl31" "Hspa8" "Coro1a"
## [93] "Hsp90ab1" "Btf3" "Atp5e" "Eef1d"
## [97] "Uba52" "Rps18" "Hint1" "Eif3h"
## [101] "Pfdn5" "Fth1" "Nsa2" "Uqcrh"
## [105] "Mif" "Eif3k" "Gstp1" "Rps17"
## [109] "Myl12b" "Rexo2" "Npc2" "Fbl"
## [113] "Psmb8" "Cox8a" "Snrpg" "Eef1g"
## [117] "Srm" "Grcc10" "Apex1" "Hspe1"
## [121] "Atp5l" "Cox7a2l" "Nop10" "Ldha"
## [125] "Tomm7" "Eif1" "Bola2" "Sec61b"
## [129] "Eif3i" "2410006H16Rik" "Ppib" "C1qbp"
## [133] "Nme1" "Ost4" "Aprt" "Krtcap2"
##
## $`5`
## [1] "Ncr1" "Tyrobp" "Fcer1g" "Klrk1" "Klrb1c" "Klre1"
## [7] "S1pr5" "Plek" "Klrb1a" "Klri2" "Gzma" "Aoah"
## [13] "Anxa1" "Gzmb" "Tbx21" "Il18rap" "Klra8" "Klra3"
## [19] "Klrb1f" "Tnfsf12" "Klrc1" "Klrc2" "Zeb2" "Klra9"
## [25] "Cma1" "Itga2" "Klra7" "Arsb" "Klra4" "Fgl2"
## [31] "Olfm1" "Dapk2" "Ccr2" "Bhlhe40" "Adamts14" "Klrb1b"
## [37] "Cd244a" "Fasl" "Sytl3" "Clnk" "Scimp" "Cd9"
## [43] "Kcnj8" "Ccl3" "Id2" "Gsap" "Klrg1" "Gem"
## [49] "Ctla2b" "Tmem37" "Lrrk1" "Arl4d" "Il12rb2" "Lat2"
## [55] "Clip4" "Styk1" "Itgam" "Plscr4" "Cdk14" "Klhl30"
## [61] "Pik3ap1" "Phactr3" "Cdc20b" "Sulf2" "Ccl4" "Osbpl3"
## [67] "Fcgr2b" "Cmklr1" "Nrarp" "Gas7" "Rap1gap2" "Klri1"
## [73] "Adgrl4" "Tmem163" "Gm33104" "Rbpms" "Sept5" "Eya1"
## [79] "Rac3" "Pdgfb" "Klrc3" "Unc79" "Itgax" "Tnfaip2"
## [85] "Gm19585" "Rasl12"
##
## $`6`
## [1] "Gtf2h4" "Ldhb" "Ctsl" "Cd8a"
## [5] "Cd8b1" "Dntt" "Ccr9" "Arpp21"
## [9] "Gm4258" "Rag1" "Cd4" "Themis"
## [13] "Glcci1" "Satb1" "Rmnd5a" "Ccnd3"
## [17] "Hmgb1" "Spint2" "Ets2" "Endou"
## [21] "Tcf7" "Ap3s1" "Trbc2" "Trac"
## [25] "Ssbp2" "Arl5c" "Ramp1" "Chrna9"
## [29] "Thy1" "H3f3b" "Rag2" "Cyb5a"
## [33] "Xrcc6" "Rorc" "Gm15340" "Sox4"
## [37] "Anxa2" "Lck" "Trbc1" "Desi1"
## [41] "H3f3a" "Edem1" "Ly6d" "Znrf1"
## [45] "Malat1" "Myb" "Colq" "Camk4"
## [49] "Sla" "Mier1" "Lat" "Sh2d1a"
## [53] "Gm38405" "Xrra1" "Slc16a5" "Tcf12"
## [57] "Trp53inp1" "Atl2" "Btg2" "Rsrp1"
## [61] "2610307P16Rik" "Ntrk3" "Abi3" "Ly6e"
## [65] "Rgcc" "Prrt1" "Mad1l1" "Dck"
## [69] "Prkcb" "Tctex1d1" "Nebl" "Cd3e"
## [73] "Clk3" "Agfg2" "Stx6" "F13a1"
## [77] "Trp53i11" "Cdca7" "Zfp280d" "Cux1"
## [81] "P2rx1"
##
## $`7`
## [1] "Nkg7" "Ctsw" "Il2rb" "Prf1"
## [5] "Ifitm10" "Eomes" "Samd3" "Cd7"
## [9] "Cst7" "Ctla2a" "Ccr5" "Zyx"
## [13] "Cxcr6" "Hopx" "1700025G04Rik" "Xcl1"
## [17] "Lsamp"
##
## $`8`
## [1] "1500009L16Rik" "Ifitm2" "Myl10" "Gm4632"
## [5] "Il2ra" "Uaca" "Ccdc18" "2700054A10Rik"
## [9] "Ptcra" "Fkbp5" "Fads2" "Epb41l4b"
## [13] "Myc"
##
## $`9`
## [1] "Zbtb16" "Tcrg-V1" "Trpm6" "Fam129a" "Il4" "Vdr" "Izumo1r"
## [8] "Ccr10" "Ccn4" "Chn2" "Gfra4"
##
## $`10`
## [1] "Ccl5" "Klrd1" "Myo1f" "Pglyrp1" "Slamf7" "Ly6c2" "Ly6c1"
##
## $`11`
## [1] "Actb" "Pfn1" "Actg1" "Arhgdib" "Cfl1" "Sh3bgrl3" "Serf2"
##
## $`12`
## [1] "Tcrg-V4" "Trgv2" "Tcrg-C4" "Tcrg-C2" "Tcrg-C1" "Pdcd1" "Plac8"
##
## $`13`
## [1] "Il23r" "Pxdc1" "Mmp25" "Serpinb1a" "Ccr6" "Gm15868"
## [7] "Adamts2"Idents(miceWT)<-"manual.annotation"
miceWT@active.ident <- factor(miceWT@active.ident,levels=c("DN","DPblast","DPsm-CD25+","DPsm-CCR7+","DPsm","DP69int","DP69+","SP4","SP8","Tgd","NK"))
plot_ggheatmap(miceWT_scigenex20.3,
use_top_genes = FALSE,
ident=Idents(miceWT)) + ggtitle("Heatmap of Co-Expressed Gene Modules Identified by SciGeneX (k = 20, inflation= 3)")
miceWT_scigenex20.3 <- enrich_go(miceWT_scigenex20.3, specie = "Mmusculus", ontology = "BP")
plot_clust_enrichments(miceWT_scigenex20.3, gradient_palette=colors_for_gradient("Je1"),
floor=50,
nb_go_term = 2) +
theme(axis.text.y = element_text(size=12))
#Assign cell types to cells in merged object based on scigeneX’s gene modules and ADT data
palette1 <- as.character(paletteer::paletteer_d("ggsci::green_material", n = 10))
names(palette1) <- c("DN","DPblast(WT)","DPsm(WT)","DPsmCD25+(WT)","DPsmCCR7+(WT)","DP69(WT)","SP8(WT)","SP8CD69+(WT)","SP4(WT)","SP4CD69+(WT)")
palette2 <- as.character(rev(paletteer::paletteer_d("ggsci::red_material", n = 4)))
names(palette2) <- c("DPblast Myc+","DPsm Myc+","DP69 Myc+","SP8 Myc+")
palette3 <- c("#7CB342FF","#689F38FF","#558B2FFF","#33691EFF")
names(palette3) <- c("NK","Tgd early","Tgd mature","MAIT")
palette4 <- as.character(paletteer::paletteer_d("ggsci::uniform_startrek", n = 1))
names(palette4) <- "Myc+"
ggplotly(DimPlot(bc.combined.cc, group.by = "sig.annotation", reduction = "wnn.umap", cols = c(palette1,palette2,palette3,palette4), label =T, label.color = "black",label.size = 5, pt.size = 0.5, repel =TRUE))## Warning in geom2trace.default(dots[[1L]][[1L]], dots[[2L]][[1L]], dots[[3L]][[1L]]): geom_GeomTextRepel() has yet to be implemented in plotly.
## If you'd like to see this geom implemented,
## Please open an issue with your example code at
## https://github.com/ropensci/plotly/issuesBALB/c TCR analysis
#Script : Immcantation_BalBC.Rmd
OTIIpalette <- c("#FDE725FF","#414487FF","#DE4968FF","#22A884FF","#7AD151FF","#808080FF")
names(OTIIpalette) <- c("OTII","OTII - TCRB incomplete","OTII - TCRA incomplete","OTII multichains","non OTII","unknown")
DimPlot(bc.combined.cc, group.by = "OTIIstatus",split.by = "OTIIstatus", reduction = "wnn.umap", cols = OTIIpalette, pt.size = 0.5)